In the year 2017, the HR technology space received around USD 1.08 billion dollars in VC investment in around 144 companies. The biggest recipient of this investment in dollar terms was talent acquisition receiving 52 percent of this investment. Within talent acquisition space, close to 40% of the money was invested in job boards and marketplaces. If you closely look at the VC money invested HR tech start-ups in talent acquisition, you would notice that most of them are either using or trying to implement artificial intelligence (AI), Machine learning (ML) and Robotics technologies to fundamentally change the way recruitment is done.
These technologies are primarily being used to help recruiters do their job more effectively and efficiently, but are also being used for the candidates to find most relevant jobs. These are very early days, as these technologies and HR Tech companies might be few years behind in terms of the application of these technologies, as compared to other enterprise applications. We believe that these technologies will have their biggest impact in HR in the talent acquisition activities.
In this report, we try and look at current and future use cases of these technologies in the talent acquisition space and how they will fundamentally change the role of the recruiter.
Artificial intelligence (AI) is a machine that can mimic human abilities such as learning, problem-solving, planning, perception and the ability to move objects. AI typically requires large amounts of data as input to produce an output which solves a particular problem. Core areas within AI include Machine learning (ML), machine perception and robotics.
AI for recruitment is essentially applying these technologies to the recruitment function. These technologies are used to streamline, automate or even eliminate certain parts of the recruitment process. In most cases today, these technologies help the recruiter by completing repetitive and high volume tasks based on defined rules. The software program can also be devised to learn from past choices, thus making it more intelligent and even prescriptive.
We now look at specific areas within the overall recruitment process and identify existing solutions that help solve a particular problem. We also look at potential uses of AI and related technologies in each of these areas.
The manpower planning process
Deloitte’s Global Human Capital trends report of 2015confirmed that only 5 percent HR professional believed that their workforce planning process is “excellent”, while one third said its “adequate” and nearly 60 percent called it “Weak”.
This is one area where we believe HR tech can support HR leaders become more aligned with their finance counterparts and truly realizes the strategic role of HR. With tools from SAP Success Factors, Workday, Oracle Hyperion Workforce Planning, and People Fluent companies today can tackle the problems of workforce planning more effectively than earlier. While there are existing models like Human Capital Institutes, Strategic Workforce planning the HR technology tools available are not necessarily aligned to such models, thus presenting a gap in the solution space.
Standalone solutions like Visier workforce planning and CEB TalentNeuron are also available in the market that helps companies even look at external labor market data and skills.
The job description
Once you have an approved hiring plan in place, the next step is to start building a job description that succinctly describes the position and makes it attractive to the potential candidates. This is very similar to be able to write an effective job advertisement that can help companies attract the relevant talent in a crowded talent market. Until recently, most recruiters would depend on internal sources to draft an effective job description (JD).
But now, technology tools like Textio help recruiters analyze the performance of their JD by comparing the same with millions of JD’s. It then recommends the use of specific words that would help improve the performance of the JD, thus ensuring you get more relevant job applications. It has claimed to help companies hire more relevant talent faster and even help them improve their gender ratio by using appropriate words.
A similar tool using AI exists for candidates and it helps them to write compelling resumes with personalized insights. It’s called Resume assistant and is brought out by Microsoft Word, powered by Linkedin. By combining the power of Word and Linkedin, the tool makes available a large amount of public data in your hand, allowing you to make more informed decisions about what kind of words to use in your profile that would make you more attractive for relevant positions. The tool seamlessly integrates with Linkedin allowing Office 365 users to use Linkedin features right from their MS Word window.
Once you have the JD ready, the next big task in all recruitment process is to ensure that you are able to source the right type of talent from multiple sources. With over a 100 different job boards and social media networks available to source talent, sourcing has become even more difficult than it was before. However, this activity thus lends itself perfectly to the use of AI and we are already noticing some interesting use cases of AI in this space.
Companies like Glider.ai, Entelo, Mya Systems, Arya by leoforce, Belong, Param.ai, Ideal, Gloat (previously Workey), Restless Bandit, Karen.ai, Drafted, RAI by HiringSolved are some of the solutions These solutions help companies automate the process of sourcing candidates from various talent pools available within and outside the company. Most of these companies use the job descriptions and past data of having hired similar profiles to make recommendations of candidates.
In some cases, such systems can also automatically contact the candidate and do an initial screening using chatbots to ensure that only the ones who are really interested and available for the position are the ones that the recruiter is talking to. We reckon that as this technology matures, it will soon become the new normal where invariably the first contact of the candidate with the company is via chat bots powered by AI.
Many companies are likely to make use of AI in the Candidate relationship management (CRM) area as recruiting gets more competitive. In the CRM space, companies are likely to depend on AI-powered solutions to ensure the job positions are effectively and attractively advertised on the most relevant job boards and social media sites.
They are then going to depend on AI-powered tools to engage candidates in initial conversations before they advance to a human interaction. This sounds very similar to the way customer service has evolved, and as consumers, we have gotten comfortable to encounter a machine first before we make our way to the human on the other end of the telephone. Recruitment is likely to go down a similar path.
Scheduling, interviewing and assessing
In these steps, the recruiter has to ensure that available candidates are scheduled for interviews with the hiring manager and also ensure that they set up the entire recruitment process which may include various types of assessments of the candidate. Currently available tools in the market help recruiters automate most of these processes. HR tech companies like HireVue, Paradox Olivia, Talview, Pomato, HireMojo, MRoads, Pymetrics, Wade and Wendy, Gecko use the Video InterviewBots.They help companies automatically schedule, set up interviews and even assess candidates based on pre-defined criteria. This automation frees up valuable time for the recruiter to focus on other value-added tasks.
Offer and Onboarding
“Think of a recruiter’s role in the future as having a job with two parts. One is the oversight of the technology needed to hire employees and ensuring that it is adapted to the organization’s needs. The second part is focused on helping new hires integrate into the organization. The second part is more difficult and adds more value than anything recruiters do today.” said Raghav Singh, Director, Reporting, and Analytics at Korn Ferry Futurestep
Another important part of recruitment is ensuring that you make a competitive offer to the candidate and then stay connected till the person joins. We see that the current HR technology space does not address this effectively. One of the solutions in this space is Oracle HCM Cloud. It has an AI Powered recruitment module which helps predict candidate offer acceptance.
While making an offer is part of the most applicant tracking system (ATS) features, not many are making use of existing and past data within the company to ensure the offer being made has a higher probability of success. We reckon these tools will evolve to start recommending offers and benefits that would make sense to the candidate depending on various socio-economic parameters.
In the onboarding process, while we see a lot of platforms in this space, they are currently mostly focused on automation of the entire onboarding process. SAP Success Factors has, however, launched an AI-powered “Onboarding buddy,” which helps companies set up answers to typical questions employees may have on the day of their joining. Many other companies like Ramco, Workday, PeopleStrong, and Infor are also making use of AI-powered technologies to drive talent decisions and help companies in simplifying HR processes especially for recruiting and onboarding talent.
We see a lot of activity in the talent acquisition space and expect the same to continue. We expect that increasingly most solution providers will start to take an end-to-end view of the recruitment process and look to build, acquire or integrate relevant solutions in their platform. This will bring even more data which would then make the AI-powered processes even more efficient and effective. We see a great future for use of AI in Talent acquisition processes and we see the role of the recruiter to fundamentally change.
With more use of technology in recruitment, the hiring managers are likely to use most technology tools in Do It Yourself (DIY) mode, thus recruiters will have to focus on building employer brand and building deeper relationships with required candidate pools.